Fund Choice Based on Behavior

Fund Choice Based on Behavior

BBVA Asset Management, the investment management arm of BBVA Group, has adopted a decision-making framework aimed at enhancing objectivity while recognizing human psychology. This approach is designed to mitigate emotional and cognitive biases that can impact investment decisions, especially in today's fragmented and volatile macro environment.

The investment strategies at BBVA Asset Management are structured around two key horizons: strategic asset allocation with a three- to five-year outlook and tactical allocation spanning one to nine months. The strategic asset allocation is focused on long-term valuation, while the tactical allocation is driven by dynamic, quantitative signals.

To reinforce discipline and consistency, BBVA Asset Management employs quantitative tools. However, these tools are used to supplement, rather than replace, human judgment. This balance between data-driven insights and expert oversight reduces bias and ensures a well-rounded approach to investment decisions.

BBVA has developed a global data platform (ADA) integrated with advanced technologies such as Amazon SageMaker. This platform enables consistent, real-time data analytics and predictive modeling that enhance strategic decision-making and operational efficiency in investment processes. The AI infrastructure supports data scientists and analysts in applying machine learning to anticipate market trends and customer needs more accurately, indirectly reducing biases by relying on data-driven signals rather than solely human intuition.

In alternatives, BBVA Asset Management applies strict criteria to ensure only liquid, transparent, and robust long-short strategies are included. Private markets and alternative risk premia are additional areas of focus for the asset manager.

Diversification across return sources and maintaining a transparent and methodical process are central to BBVA Asset Management's strategy. Institutional clients of BBVA Asset Management have moved their equity benchmarks to climate transition benchmarks, reflecting a growing focus on climate-related risks in long-term strategic allocation decisions.

BBVA Asset Management has redesigned the governance framework for selecting private market investments using behavioral principles to address groupthink and improve objectivity and accountability. The asset manager also caps private markets exposure for retail portfolios at around 3-4%, favouring investments with shorter durations and higher cash distributions.

Incorporating AI and machine learning has been part of the evolution at BBVA Asset Management. Tools like the US Equity Scorecard model and a dynamic asset allocation model covering 21 asset classes are used to enhance the investment process. BBVA Asset Management has also developed an internal ESG rating system that applies universally across all portfolios.

The asset manager is active in voting and engagement in regards to ESG issues. They have introduced goal-based model portfolios as part of its discretionary portfolio management, and tactical decisions are primarily made using rule-based models to reduce the impact of behavioral biases.

In summary, BBVA Asset Management's approach to investment decisions is grounded in a structured behavioural economics framework combined with AI-powered quantitative tools and a scalable global data platform. This strategy aims to deliver disciplined, transparent, and data-informed investment decisions while mitigating emotional and cognitive biases.

[1] BBVA Asset Management. (2021). BBVA Asset Management deploys AI to improve investment decision-making. Retrieved from https://www.bbva.com/en/news-and-media/bbva-asset-management-deploys-ai-to-improve-investment-decision-making/

[3] BBVA Asset Management. (2021). BBVA Asset Management launches its new ESG rating system. Retrieved from https://www.bbva.com/en/news-and-media/bbva-asset-management-launches-its-new-esg-rating-system/

1. BBVA Asset Management leverages technology, such as Amazon SageMaker, to enhance real-time data analytics and predictive modeling, assisting in the reduction of biases by relying on data-driven signals rather than solely human intuition.
2. In private markets and alternative risk premia, BBVA Asset Management implements strict criteria to include only liquid, transparent, and robust strategies, while limiting exposure for retail portfolios.
3. To manage behavioral biases in the investing process, BBVA Asset Management employs rule-based models for tactical decisions in goal-based model portfolios, and uses an internal ESG rating system that applies universally across all portfolios.

Read also: